class_docstr: The LogisticRidgeRegression class is used to fit logistic ridge regression models against one or more labels optimized over a
  provided list of ridge alpha parameters. The optimal ridge alpha value is chosen for each label by minimizing the
  average out of fold log_loss scores.
docstr: Initializes an instance of LogsiticRidgeRegression using a RidgeReduction object
  
  Args:
      ridge_reduced : A RidgeReduction instance based on which the LogisticRidgeRegression instance must be made
      alphas : array_like of alpha values used in the logistic ridge regression (optional).
docstr_tok: ["Initializes","an","instance","of","LogsiticRidgeRegression","using","a","RidgeReduction","object","Args",":","ridge_reduced",":","A","RidgeReduction","instance","based","on","which","the","LogisticRidgeRegression","instance","must","be","made","alphas",":","array_like","of","alpha","values","used","in","the","logistic","ridge","regression","(","optional",")","."]
code: def from_ridge_reduction(
      cls, ridge_reduced: RidgeReduction, alphas: List[float] = []
  ):
      """
      Initializes an instance of LogsiticRidgeRegression using a RidgeReduction object
  
      Args:
          ridge_reduced : A RidgeReduction instance based on which the LogisticRidgeRegression instance must be made
          alphas : array_like of alpha values used in the logistic ridge regression (optional).
      """
      obj = cls.__new__(cls)
      obj.reduced_block_df = ridge_reduced.reduced_block_df
      obj.sample_blocks = ridge_reduced.sample_blocks
      obj._label_df = ridge_reduced.get_label_df()
      obj._cov_df = ridge_reduced.get_cov_df()
      obj._std_cov_df = ridge_reduced._std_cov_df
      obj.set_alphas(alphas)
      obj.model_df = None
      obj.cv_df = None
      obj.y_hat_df = None
      return obj
  
imports: from .logistic_udfs import *
  from .ridge_reduction import RidgeReduction
  from .model_functions import _prepare_labels_and_warn, _prepare_covariates, _check_model, _check_cv, _is_binary
  from nptyping import Float, NDArray
  import pandas
  from pyspark.sql import DataFrame
  from pyspark.sql.functions import pandas_udf, PandasUDFType
  import pyspark.sql.functions
  from typeguard import typechecked
  from typing import Any, Dict, List
  import warnings
  from glow.logging import record_hls_event
label_desc: Use image node_id 2 for calling the LogisticRidgeRegression obj's underlying member method code with example usage: obj.from_ridge_reduction(cls, ridge_reduced, alphas) and returns: obj